Nils Hammerla

nils.hammerla@ncl.ac.uk | Research Associate

Nils Hammerla

A common setting in Activity Recognition is that sensors, such as triaxial accelerometers, are worn on the body or embedded into objects of daily use. The recorded multi-variate sensor streams undergo analysis in order to infer the activities that were performed by the user. Simple yet effective methods, such as k-NN classification using statistical features, often suffice to obtain impressive recognition accuracies. Therefore information about what subjects are doing is readily available, rendering activity segmentation a straight-forward followup task. However, so far relatively little work was invested into a further, detailed analysis of these segmented activities, although extracting their characteristics, i.e. how well these activities were performed, would be beneficial to a variety of applications spanning many domains.
My main research goal is to develop novel methods for the assessment of this motor skill, particularly for applications in medicine. Here many degenerative conditions such as Parkinson’s Disease and Dementia have a significant impact on motor abilities, where motor assessment is crucial for early intervention and treatment.

 

Homepage: http://homepages.cs.ncl.ac.uk/nils.hammerla/


FAILED TO QUERY
This person has not yet published at this institution.

Associated Projects

  • Diri - the actuated helium balloon: a study of autonomous behaviour in interfaces
    As the sophistication of ubiquitous computing technologies increases, with advances in processing power and decreases in size users are being confronted with increasingly intelligent interfaces embedded in everyday devices. This raises an inter...
    August 30, 2011
  • Touchbugs: Actuated Tangibles on Multi-Touch Tables
    Touchbugs is an open source hardware and software framework for a novel actuated tangible technology. Touchbugs are small tangibles that use directed bristles and vibration motors for actuation (giving them the ability to move independently). Their inf...
    August 30, 2011
  • Activity Recognition to Improve Motor Performance in Parkinson's Disease
    Through sensors worn on the body or embedded into objects of daily use we can infer the activities performed by a subject. Extracting the characteristics of the data collected by these sensors, i.e. how these activities were performed, would be ben...
    August 30, 2011
  • ACCEL-O-SURG
    The aim of this project was to understand the changes in motor skill that take place during the early phases of learning a new fine motor skill task. For this project specifically, that motor skill was suturing, which we measured by attaching senso...
    August 30, 2011
  • Quantifying Human Motion for Medical Applications
    Often, high accuracy activity recognition can be performed using relatively simple methods, such as through the use of sensors like accelerometers and gyroscopes. This means that activity segmentation, meaning the extraction of continuous sequences...
    August 30, 2011
  • Cueing for Swallowing in Parkinson's
    This cueing device has been developed as a way to behaviourally manage drooling, which is commonly symptomatic of Parkinson’s Disease. The device was developed through a participatory design process, taking into account the needs of people with Parki...
    August 30, 2011
  • Cueing Technology for Parkinsons
    Approximately 70% of people with Parkinson’s Disease experience problems with swallowing. The resulting build-up of saliva can cause drooling, which is often a source of embarrassment and puts the person at risk of choking or pneumonia if the saliv...
    August 30, 2011
 
Copyright 2015 Open Lab